Sentence Similarity
sentence-transformers
Safetensors
roberta
feature-extraction
Generated from Trainer
dataset_size:10501
loss:CosineSimilarityLoss
Eval Results (legacy)
text-embeddings-inference
Instructions to use LeeGH04/klue-roberta-base-klue-sts with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- sentence-transformers
How to use LeeGH04/klue-roberta-base-klue-sts with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("LeeGH04/klue-roberta-base-klue-sts") sentences = [ "아울러 데이터 활용에 따른 개인정보 처리자의 책임을 강화했다.", "또한, 데이터 활용에 따른 개인정보처리 담당자의 책임도 강화하였습니다.", "다시 베니스에 방문한다면 반드시 재 예약할 숙소에요", "지금 잡혀 있는 내일 오후 일정 개수가 얼마나 되나?" ] embeddings = model.encode(sentences) similarities = model.similarity(embeddings, embeddings) print(similarities.shape) # [4, 4] - Notebooks
- Google Colab
- Kaggle
Welcome to the community
The community tab is the place to discuss and collaborate with the HF community!